目的:運用主成分分析球隊之整體技術表現型態,並與單項技術表現比較,且觀察是否與最終比賽排名有關。方法:以第13季(2017-2018)臺灣企業甲級排球聯賽官方網站上公布之詳細攻守數據為資料,總計96場賽事(男子組5隊各24場、女子組4隊各18場)為範圍,將球隊之6項技術的成功率做為單項技術表現,以單因子變異數分析進行比較,並將各隊每場次的6項技術與得分之原始分數與成功率共14項資料進行主成分分析。結果:攻擊、攔網為主要比賽勝負因素,女子組的舉球技術則是進一步影響排名的主因。資料可簡化為3-4個成分數,達78-88%的累積解釋量;女子組以得分技術型態為第一主成分,但各隊有明顯不同特色(接發進攻、防守反攻),且技術串聯有落差;男子組則以非得分技術型態(接發、舉球、防守)為主。隊伍的得分多以攻擊為串聯技術,發球技術並非比賽的主要表現型態。結論:本研究利用單項技術表現與主成分分析表現型態,描繪出球隊特色與比賽勝負之關聯,有全面透過官方數據檢討比賽的助益。未來研究可探討單一隊伍之勝負場次差異、不同比賽層級之差異。
Purpose: This study aimed to explore the team's overall technical performance pattern by utilize principal component analysis (PCA) and compared with the single technical performance to see if there was relevant to the final competition ranking. Methods: The scope was based on the detailed offensive and defensive data published on the official website of the Taiwan Top Volleyball League (TVL) in the 13th season (2017-2018), and a total of 96 games (24 in each of the men's five teams, 18 in each of the women's four teams) were analyzed. The success rate of six volleyball techniques of the team represented as technical performance, which were compared by one-way independent ANOVA. The scores and the points of six volleyball techniques were calculated by each team per match, and then 14 sources (the original data and its success rate) were following the exploration of technical performance pattern by PCA. Results: Attack and block were the main techniques affecting the competition ranking, and set also influenced women's team raking. The data can be reduction to 3-4 components and explained 78-88% variances by PCA. The first component (PC1) of women's teams were the scoring technique pattern, but there were different patterns between the teams (receive to attack, defensive-counterattacks), and the series of techniques. The PC1 of men's teams were the non-scoring techniques (receive, dig and set). The score was frequently linked to attack, and serve was not the main factor of the game. Conclusions: The present study showed that using technical performance and technical performance pattern by PCA could effectively depict the relationship between the team's characteristics and the outcome of the game, which was helpful to have a comprehensive review of the game through the official data. Future researches were suggested to explore the differences between win and lose matches of a single team, and the differences of competition level.